Tuning of PPO metaparameters: a high level overview of what each parameter does
Some investigation about the memory dict: The current type is latest, which means you're not using a memory replay, but a latest memory. Switching to replay may help.
Also, include_next_state means that you store tuples (state, action, reward, next state). It's not a real parameter though, because in PPO it must be set to False, otherwise an error is raised.
Your interpretation of capacity looks OK.

About the update mode spec dict, your current settings mean that : every 10 (frequency) episodes (unit), you pull a batch of 10 (batch_size) episodes (unit) from the memory (the pulling method is defined through the memory dict), and you perform an optimization step over this batch. Be aware that the unit defines both the unit of the optimization frequency and the type of the object fetched from the memory.